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Nano Banana Pro (Gemini 3 Pro Image Preview): pricing, context and benchmarks

Nano Banana Pro (Gemini 3 Pro Image Preview) is a language model from Google released on November 20, 2025. It costs $2 per million input tokens and $12 per million output tokens, with a 65.5K-token context window. No independent score has been published for it so far.

Score
20/100
Price 4/30
Context 2/15
Features 6/15
High costReasoningNo tool calling

What you need to know about Nano Banana Pro (Gemini 3 Pro Image Preview)

Nano Banana Pro (Gemini 3 Pro Image Preview) was released by Google (United States) on November 20, 2025. It accepts images and text as input and produces images and text. Its context window reaches 65,536 tokens, larger than 12 % of the models in the registry, and it can write up to 32,768 tokens in one go.

It has been available for about 11 months, long enough for its prices and scores to have settled.

Nano Banana Pro (Gemini 3 Pro Image Preview) pricing

On OpenRouter, Nano Banana Pro (Gemini 3 Pro Image Preview) costs $2 per million input tokens and $12 per million output tokens. Counting three tokens read for every token written, its average price is $4.5 per million, more expensive than 88 % of paid models (5.9 times the median of $0.76).

A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.01. At 1,000 tasks a day, budget $300 a month. The price calculator redoes this with your own volumes.

Tokens already sent and cached are billed at $0.2 per million.

Performance and benchmarks

Epoch AI does not yet publish a capabilities index for Nano Banana Pro (Gemini 3 Pro Image Preview). We therefore show no made-up performance rating: only price, context and features count towards its score.

Features, privacy and local use

  • It does not support tool calling: it is not suited to driving an AI agent that has to act.
  • It can answer in an enforced JSON format (structured outputs).
  • It is a reasoning model: it "thinks" before answering, which helps on hard tasks but uses more output tokens.

Its weights are not published: it can only be used through the Google API or a broker such as OpenRouter, which means sending your data off your machines.

Other Google models

Average price per million tokens (3 input for 1 output).
ModelReleasedAvg. priceECI
Gemini 4 ArgonOct 13, 2026$4166.5
Nano Banana 2.1Oct 6, 2026$3—
Gemini 3.8 FlashSep 2, 2026$1.65157.4
Gemini 3.7 FlashAug 13, 2026$1.5158
Gemini 3.6 FlashJul 21, 2026$1.5154.5
Gemini 3.5 Flash LiteJul 21, 2026$0.85144.9
Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)Jun 30, 2026$0.56—
Nano Banana 2 (Gemini 3.1 Flash Image)Jun 18, 2026$1.13—

Verdict

Nano Banana Pro (Gemini 3 Pro Image Preview) scores 20/100 on our grid, which only uses published figures.

Limitations

  • Expensive: costlier than 88 % of paid models.
  • No tool calling: unusable as an agent's brain.
  • No independent score published: performance cannot be verified.

Avoid if…

  • you process large volumes on a tight budget;
  • your data must not leave your servers;
  • you are building an agent that must call tools;
  • your tasks are mostly simple: a non-reasoning model will cost less.

Frequently asked questions

How much does Nano Banana Pro (Gemini 3 Pro Image Preview) cost?

$2 per million input tokens and $12 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.01.

How big is Nano Banana Pro (Gemini 3 Pro Image Preview)'s context window?

65,536 tokens, roughly 49,000 words, with a maximum of 32,768 output tokens.

Can Nano Banana Pro (Gemini 3 Pro Image Preview) run locally?

No, Google does not publish its weights: it is API-only.

Is Nano Banana Pro (Gemini 3 Pro Image Preview) suitable for an AI agent?

No: without tool calling it cannot act, only answer.

What are the alternatives to Nano Banana Pro (Gemini 3 Pro Image Preview)?

The closest models on price and performance are GPT-5.2 Chat, GPT Audio, and GPT-4o (2024-11-20).

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score